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Careers

At Amazon, we believe that scientific innovation is essential to being the most customer-centric company in the world. Our scientists' ability to have an impact at scale allows us to attract some of the brightest minds across diverse fields including artificial intelligence, robotics, computer vision, economics, and sustainability. Join us in pioneering solutions to complex challenges that not only delight our customers but also help define the future of technology.
  • The program is designed for academics from universities around the globe who want to work on large-scale technical challenges while continuing to teach and conduct research at their universities.
  • The program offers recent PhD graduates an opportunity to advance research while working alongside experienced scientists with backgrounds in industry and academia.
  • Our internship roles span research areas to provide hands-on experience working alongside world-class scientists and engineers to advance the state of the art in your field.
654 results found
  • US, MA, Boston
    Job ID: 3166902
    (Updated 105 days ago)
    Join Amazon Global Logistics (AGL) as a Senior Data Scientist on our Pricing & Science team. You'll develop machine learning models, AI agents, and optimization systems that serve businesses of all sizes in cross-border logistics. This role combines advanced machine learning with hands-on execution to establish AGL as a leading global freight provider. You'll work on high-impact initiatives including agentic AI systems that drive marketing effectiveness and enable data-driven sales decisions, ML-powered fraud and theft detection models to protect Amazon's supply chain, revenue management systems incorporating real-time market signals and capacity constraints, and economic value models to quantify the business impact of logistics capabilities. Key job responsibilities - Collaborate with product, engineering, operations, and security teams to translate business problems into production-ready solutions - Own end-to-end model development from exploratory analysis to deployment and monitoring - Define, track, and explain success metrics to measure model impact and inform decision-making - Build business cases to support science initiatives and model prioritization - Develop ML-powered systems for marketing effectiveness, fraud detection, revenue management, and economic value modeling - Write technical papers and submit work to internal and external conferences and publications A day in the life Your day might start with improving theft detection model accuracy. You'll collaborate with scientists to enhance features for pricing models. You'll connect with stakeholders in international markets to evaluate new agentic marketing solutions. You'll sync with applied scientists and engineering teams on productionizing models. You'll meet with operations to understand capacity forecasts and routing constraints. You'll work with security teams on theft detection workflows. You'll design new modeling approaches, run experiments, and present recommendations to stakeholders. The role offers strategic thinking, hands-on model development, and tactical analysis in a fast-paced environment where you'll own significant technical initiatives. About the team The AGL Pricing & Science team operates at the intersection of science, logistics, and business strategy. We're a diverse group of problem-solvers working to transform international freight forwarding. Our team builds intelligent pricing systems, predicts and prevents seller churn, develops GenAI applications for operational intelligence, creates ML-powered fraud detection systems, builds routing optimization models, and prioritizes seller experience. We value data-driven decision making and innovation. Our work protects millions in GMS and drives hundreds of millions in cost savings annually. We offer opportunities to make significant impact while working with AI technologies and systems at Amazon scale.
  • (Updated 8 days ago)
    Alexa+ is Amazon’s next-generation, AI-powered virtual assistant. Building on the original Alexa, it uses generative AI to deliver a more conversational, personalised, and effective experience. Alexa Sensitive Content Intelligence (ASCI) team is developing responsible AI (RAI) solutions for Alexa+, empowering it to provide useful information responsibly. The Mission Build AI safety systems that protect millions of Alexa customers every day. As conversational AI evolves, you'll solve challenging problems in Responsible AI by ensuring LLMs provide safe, trustworthy responses, building AI systems that understand nuanced human values across cultures, and maintaining customer trust at scale. What You'll Build You'll pioneer breakthrough solutions in Responsible AI at Amazon's scale. Imagine training models that set new safety standards, designing automated testing systems that hunt for vulnerabilities before they surface, and certifying the systems that power millions of daily conversations. You'll create intelligent evaluation systems that judge responses with human-level insight, build models that truly understand what makes interactions safe and delightful, and craft feedback mechanisms that help Alexa+ grasp the nuances of complex customer conversations. Here's where it gets even more exciting: you'll build AI agents that act as your team's safety net—automatically detecting and fixing production issues in real-time, often before anyone notices there was a problem. Your innovations won't just improve Alexa+; they'll fundamentally shape how it learns, evolves, and earns customer trust. As Alexa+ continues to delight customers, your work ensures it becomes more trustworthy, safer, and deeply aligned with customer needs and expectations. Your work directly protects customer trust at Amazon's scale. Every innovation you create—from novel safety mechanisms to sophisticated evaluation techniques—shapes how millions of people interact with AI confidently. You're not just building products; you're defining industry standards for responsible AI. This is frontier research with immediate real-world impact. You'll tackle problems that require innovative solutions: training models that remain truthful and grounded across diverse contexts, building reward models that capture the nuanced spectrum of human values across cultures and languages, and creating automated systems that continuously discover and address potential issues before customers encounter them. You'll collaborate with world-class scientists, product managers, and engineers to transform state-of-the-art ideas into production systems serving millions. What We're Looking For * Deep expertise in state-of-the-art NLP, Large Language Models * Track record of building scalable ML systems * Passion for impactful research—where frontier science meets real-world responsibility at scale * Excitement about solving problems that will shape the future of AI Ready to work on AI safety challenges that define the industry? Join us. Key job responsibilities The Responsible AI (RAI) team is at the forefront of building AI systems that are safe, ethical, and trustworthy. As a Senior Applied Scientist, you'll lead the scientific vision for end-to-end Responsible AI solutions—pioneering algorithms that eliminate false information, designing frameworks that hunt down vulnerabilities before bad actors find them, and developing models that understand human values across every culture we serve. Working alongside world-class engineers and scientists, you'll push the boundaries of model training, building agentic AI systems that coordinate multiple autonomous agents to solve complex safety challenges—transforming bold research into production systems that protect millions of customers daily while withstanding attacks and delivering exceptional experiences. But here's what makes this role truly special: you'll shape the future. You'll lead efforts to identify, define, and mitigate risks early—protecting customers before they're impacted—and mentor the next generation of AI safety experts. You'll design multi-agent architectures where distributed AI systems exhibit emergent collective intelligence while maintaining human oversight and control. Every innovation you drive—from consensus-driven reasoning frameworks to sophisticated orchestration patterns—will set new standards for trustworthy AI at the world's largest scale. A day in the life As a Responsible AI Scientist, you're at the frontier of AI safety—experimenting with breakthrough techniques that push the boundaries of what's possible. You partner with engineering to transform research into production-ready solutions, tackling complex optimization challenges. You brainstorm with Product teams, translating ambitious visions into concrete objectives that drive real impact. Your expertise shapes critical deployment decisions as you review impactful work and guide go/no-go calls. You mentor the next generation of AI safety leaders, watching ideas spark and capabilities grow. This is where science meets impact—building AI that's not just intelligent, but trustworthy and aligned with human values. About the team Our team pioneers Responsible AI for conversational assistants. We ensure Alexa delivers safe, trustworthy experiences across all devices, modalities, and languages worldwide. We work on frontier AI safety challenges—and we're looking for scientists who want to help shape the future of trustworthy AI.
  • US, CA, Palo Alto
    Job ID: 3182871
    (Updated 9 days ago)
    We’re working to improve shopping on Amazon using the conversational capabilities of large language models, and are searching for pioneers who are passionate about technology, innovation, and customer experience, and are ready to make a lasting impact on the industry. You’ll be working with talented scientists, engineers, and technical program managers (TPM) to innovate on behalf of our customers. We’re looking for scientists with deep LLM expertise to help us build the next generation of large language models. Our team focuses on post-training, including instruction tuning, reward modeling, and reinforcement learning. In this role, you will design and run large-scale experiments, analyze model behavior, and develop new training recipes that directly improve core capabilities like reasoning, user experience, and other frontier paradigms that redefine what LLMs can do. If you’re fired up about being part of a dynamic, driven team, then this is your moment to join us on this exciting journey!
  • (Updated 35 days ago)
    The Amazon Publisher Monetization Stores team is seeking an experienced Manager, Applied Science to lead our Stores Supply Science team and our Stores Supply Applied Science Engineering team. In this role, you will be responsible for developing novel machine learning and optimization solutions to drive improvements in the monetization of digital content for Amazon's publishing partners. You will collaborate closely with product, engineering, and business stakeholders to identify high-impact opportunities, define technical roadmaps, and deliver innovative solutions at scale. Equally importantly you will represent APM Stores Science across the broader Ads science community (e.g. Sponsored Products, Sponsored Brands, DSP and Ads Econ) and drive collaboration and harmonization. This is an exciting opportunity to leverage your depth of applied science expertise to shape the future of Amazon's publisher monetization platform and have a significant impact on the business. Key job responsibilities * Lead the Stores Supply Science team and Applied Science Engineering teams as a direct manager, setting the technical vision and implementation, managing performance, and developing your team members * Work closely with product, engineering, and business stakeholders to define the technical roadmap and ensure the delivery of high-impact solutions * Represent APM Stores Science across the broader Ads science community * Identify new opportunities to leverage data and advanced analytics to unlock value for Amazon's publishing partners * Foster a culture of innovation, agility, and customer obsession within your teams A day in the life As the Manager, Applied Science, you will spend your time collaborating with key stakeholders, leading your teams, and driving the development and deployment of high-impact solutions. A typical day may include: * Meeting with product and business leaders to understand their challenges and align on strategic priorities * Reviewing progress and providing guidance to your direct reports on the Stores Supply Science and Applied Science engineering teams * Defining the technical roadmap and implementation plan for new models in collaboration with engineering teams * Presenting your teams' work and recommendations to senior leadership * Providing career feedback and growth opportunities to your direct reports * Staying abreast of the latest advancements in machine learning and other scientific disciplines and exploring how they could be applied to our business
  • US, WA, Bellevue
    Job ID: 3155354
    (Updated 85 days ago)
    As an Applied Scientist for Last Mile Delivery Automation, you will be at the forefront of developing AI and ML solutions that power our delivery solutions. This role combines deep expertise in machine learning, computer vision, and robotics to solve complex challenges in real-world perception, navigation, and path planning. You will work closely with applied scientists, software developers, and product teams to research, design, and implement sophisticated algorithms that enable safe and efficient operations. This position requires a unique blend of theoretical knowledge and practical implementation skills, with a focus on transforming research concepts into production-ready solutions that can operate reliably in diverse real-world environments. Key job responsibilities - Design and develop advanced machine learning models and algorithms for perception, navigation and planning. - Lead research initiatives in areas such as computer vision, sensor fusion, behavioral prediction, and path planning - Transform research concepts into production-ready solutions that meet strict safety and performance requirements - Develop novel approaches to solve complex technical challenges in perception, navigation and planning - Create and implement metrics and evaluation frameworks to measure model performance - Collaborate with engineering teams to integrate ML solutions into production stack - Publish research findings and represent Amazon at technical conferences About the team The Applied Science team within Amazon's Last Mile Delivery Automation organization focuses on developing machine learning solutions for autonomous systems. We work at the intersection of computer vision, deep learning, robotics, and control systems to create robust and scalable algorithms that enable safe autonomous operation. Our team combines expertise from diverse scientific backgrounds to tackle fundamental challenges in perception, prediction, and decision-making.
  • US, WA, Seattle
    Job ID: 3157569
    (Updated 28 days ago)
    Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by preventing eCommerce fraud? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment? If yes, then you may be a great fit to join the Amazon Selling Partner Trust & Store Integrity Science Team. We are looking for a talented scientist who is passionate to build advanced machine learning systems that help manage the safety of millions of transactions every day and scale up our operation with automation. Key job responsibilities Innovate with the latest GenAI/LLM/VLM technology to build highly automated solutions for efficient risk evaluation and automated operations Design, develop and deploy end-to-end machine learning solutions in the Amazon production environment to create impactful business value Learn, explore and experiment with the latest machine learning advancements to create the best customer experience A day in the life You will be working within a dynamic, diverse, and supportive group of scientists who share your passion for innovation and excellence. You'll be working closely with business partners and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems. You will build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation. You will also be providing clear and compelling reports for your solutions and contributing to the ongoing innovation and knowledge-sharing that are central to the team's success.
  • CA, BC, Vancouver
    Job ID: 3155455
    (Updated 71 days ago)
    The Private Brands Discovery team designs innovative machine learning solutions to drive customer awareness for Amazon’s own brands and help customers discover products they love. Private Brands Discovery is an interdisciplinary team of Scientists and Engineers, who incubate and build disruptive solutions using cutting-edge technology to solve some of the toughest science problems at Amazon. To this end, the team employs methods from Natural Language Processing, Deep learning, multi-armed bandits and reinforcement learning, Bayesian Optimization, causal and statistical inference, and econometrics to drive discovery across the customer journey. Our solutions are crucial for the success of Amazon’s own brands and serve as a beacon for discovery solutions across Amazon. This is a high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and engineers. As a scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions.. With a focus on bias for action, this individual will be able to work equally well with Science, Engineering, Economics and business teams. Key job responsibilities - Experience in causal ML and treatment effect estimation, including methods like propensity scoring, doubly robust estimators, and uplift modeling. Strong background in Python, ML pipelines, and deploying models to production with robust monitoring and evaluation. Familiarity with causal inference frameworks and translating business questions into actionable causal insights. - Drive applied science projects in machine learning end-to-end: from ideation over prototyping to launch. For example, starting from deep scientific thinking about new ways to support customers’ journeys through discovery, you analyze how customers discover, review and purchase Private Brands to innovate marketing and merchandising strategies. - Propose viable ideas to advance models and algorithms, with supporting argument, experiment, and eventually preliminary results. - Invent ways to overcome technical limitations and enable new forms of analyses to drive key technical and business decisions. - Present results, reports, and data insights to both technical and business leadership. - Constructively critique peer research and mentor junior scientists and engineers. - Innovate and contribute to Amazon’s science community and external research communities.
  • (Updated 146 days ago)
    职位:Applied scientist 应用科学家实习生 毕业时间:2026年10月 - 2027年7月之间毕业的应届毕业生 · 入职日期:2026年6月及之前 · 实习时间:保证一周实习4-5天全职实习,至少持续3个月 · 工作地点:北京朝阳区 投递须知: 1 填写简历申请时,请把必填和非必填项都填写完整。提交简历之后就无法修改了哦! 2 学校的英文全称请准确填写。中英文对应表请查这里(无法浏览请登录后浏览)https://docs.qq.com/sheet/DVmdaa1BCV0RBbnlR?tab=BB08J2 如果您正在攻读计算机,AI,ML或搜索领域专业的博士或硕士研究生,而且对应用科学家的实习工作感兴趣。如果您也喜爱深入研究棘手的技术问题并提出解决方案,用成功的产品显著地改善人们的生活。 那么,我们诚挚邀请您加入亚马逊的International Technology搜索团队改善Amazon的产品搜索服务。我们的目标是帮助亚马逊的客户找到他们所需的产品,并发现他们感兴趣的新产品。 这会是一份收获满满的工作。您每天的工作都与全球数百万亚马逊客户的体验紧密相关。您将提出和探索创新,基于TB级别的产品和流量数据设计机器学习模型。您将集成这些模型到搜索引擎中为客户提供服务,通过数据,建模和客户反馈来完成闭环。您对模型的选择需要能够平衡业务指标和响应时间的需求。
  • US, WA, Seattle
    Job ID: 3151585
    (Updated 20 days ago)
    We are looking for a talented, organized, and customer-focused applied researcher to join our Pricing Optimization science group, with a charter to measure, refine, and launch customer-obsessed improvements to our algorithmic pricing and promotion models across all products listed on Amazon. This role requires an individual with exceptional machine learning modeling and architecture expertise — particularly in deep learning, neural networks, and transformer-based architectures applied to price prediction and forecasting problems. The ideal candidate brings a strong foundation in applied statistics and probabilistic modeling, excellent cross-functional collaboration skills, business acumen, and an entrepreneurial spirit. We are looking for an experienced innovator who is a self-starter, comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work in a fast-paced and ever-changing environment. Key job responsibilities See the big picture. Understand and influence the long-term vision for Amazon's science-based competitive, perception-preserving pricing techniques. Develop and advance price prediction models leveraging deep learning frameworks, transformer architectures, and advanced statistical methods to drive pricing accuracy at scale. Build strong collaborations. Partner with product, engineering, and science teams within Pricing & Promotions to deploy machine learning price estimation and error correction solutions at Amazon scale. Design and implement neural network-based architectures — including sequence models and transformers — for large-scale price prediction and optimization. Stay informed. Establish mechanisms to stay up to date on the latest scientific advancements in deep learning, transformer architectures, applied statistics, neural network design, probabilistic forecasting, and multi-objective optimization techniques. Identify opportunities to apply them to relevant Pricing & Promotions business problems. Keep innovating for our customers. Foster an environment that promotes rapid experimentation, continuous learning, and incremental value delivery. Leverage statistical rigor and modern deep learning approaches to validate hypotheses and drive measurable pricing improvements. Successfully execute & deliver. Apply your exceptional technical machine learning expertise — including deep neural networks, attention-based models, and applied statistical analysis — to incrementally move the needle on some of our hardest pricing problems. A day in the life We are hiring a Sr. Applied Scientist to drive our pricing optimization initiatives. We drive cross-domain and cross-system improvements through: * shape and extend our RL optimization platform - a pricing centric tool that automates the optimization of various system parameters and price inputs. * Error detection and price quality guardrails at scale. * Identifying opportunities to optimally price across systems and contexts (marketplaces, request types, event periods) Price is a highly relevant input into Stores architectures; this role creates the opportunity to drive extremely large impact (measured in Bs not Ms), but demands careful thought and clear communication. About the team The Pricing Optimization science group builds and refines Amazon's algorithmic pricing and promotion models at scale. Our team combines expertise in deep learning, transformer architectures, applied statistics, and probabilistic forecasting to develop price prediction systems that directly impact the customer experience. The team also brings hands-on experience with causal modeling and inference — including uplift modeling and treatment effect estimation — to rigorously measure the impact of pricing decisions on customer behavior and business outcomes. We partner closely with product, engineering, and business teams to take solutions from research through production deployment.
  • US, CA, Santa Clara
    Job ID: 3169077
    (Updated 76 days ago)
    Join the next science and engineering revolution at Amazon's Delivery Foundation Model team, where you'll work alongside world-class scientists and engineers to pioneer the next frontier of logistics through advanced AI and foundation models. We are seeking an exceptional Applied Scientist to help develop innovative foundation models that enable delivery of billions of packages worldwide. In this role, you'll combine highly technical work with scientific leadership, ensuring the team delivers robust solutions for dynamic real-world environments. Your team will leverage Amazon's vast data and computational resources to tackle ambitious problems across a diverse set of Amazon delivery use cases. Key job responsibilities - Design and implement novel deep learning architectures combining a multitude of modalities, including image, video, and geospatial data. - Solve computational problems to train foundation models on vast amounts of Amazon data and infer at Amazon scale, taking advantage of latest developments in hardware and deep learning libraries. - As a foundation model developer, collaborate with multiple science and engineering teams to help build adaptations that power use cases across Amazon Last Mile deliveries, improving experience and safety of a delivery driver, an Amazon customer, and improving efficiency of Amazon delivery network. - Drive technical direction for specific research initiatives, ensuring robust performance in production environments. A day in the life As a member of the Delivery Foundation Model team, you’ll spend your day on the following: - Develop and implement novel foundation model architectures, working hands-on with data and our extensive training and evaluation infrastructure - Collaborate with fellow scientists in solving complex technical challenges, from trajectory planning to efficient multi-task learning - Collaborate with fellow engineers in building scalable and reusable infra to support model training, evaluation, and inference - Contribute to focused technical initiatives from conception through deployment, ensuring successful integration with production systems - Drive technical discussions within the team and and key stakeholders - Conduct experiments and prototype new ideas - Make significant hands-on contribution to technical solutions About the team The Delivery Foundation Model team combines ambitious research vision with real-world impact. Our foundation models provide generative reasoning capabilities required to meet the demands of Amazon's global Last Mile delivery network. We leverage Amazon's unparalleled computational infrastructure and extensive datasets to deploy state-of-the-art foundation models to improve the safety, quality, and efficiency of Amazon deliveries. Our work spans the full spectrum of foundation model development, from multimodal training using images, videos, and sensor data, to sophisticated modeling strategies that can handle diverse real-world scenarios. We build everything end to end, from data preparation to model training and evaluation to inference, along with all the tooling needed to understand and analyze model performance. Join us if you're excited about pushing the boundaries of what's possible in logistics, working with world-class scientists and engineers, and seeing your innovations deployed at unprecedented scale.

Science at Amazon around the world

Amazon scientists are working on large-scale technical challenges in a variety of research areas across the globe. Use the pins below to learn more about the customer-obsessed science being conducted at some of our research locations.
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Academia

Amazon collaborates with leading academic organizations to drive innovation and to ensure that research is creating solutions whose benefits are shared broadly across all sectors of society.